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			<h1><font face="georgia">Matt's Webcorner</font></h1>
			<h2>Stanford 2014</h2>
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<h1>Real-time Non-rigid Reconstruction using an RGB-D Camera</h1>
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<a href="https://www.google.com/search?q=Michael+Zollhoefer">Michael Zollhoefer</a>
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<a href="http://graphics.stanford.edu/~niessner/publications.html">Matthias Nießner</a>
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<a href="https://www.google.com/search?q=Sharam+Izadi">Sharam Izadi</a>
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<a href="https://www.google.com/search?q=Christoph+Rehmann">Christoph Rehmann</a>
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<a href="http://graphics.stanford.edu/~mdfisher/publications.html">Matthew Fisher</a>
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<a href="https://www.google.com/search?q=Chenglei+Wu">Chenglei Wu</a>
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<a href="https://www.google.com/search?q=Andrew+Fitzbiggon">Andrew Fitzbiggon</a>
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<a href="https://www.google.com/search?q=Charles+Loop">Charles Loop</a>
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<a href="https://www.google.com/search?q=Christian+Theobolt">Christian Theobolt</a>
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<a href="https://www.google.com/search?q=Marc+Stamminger">Marc Stamminger</a>
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Stanford University
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<img id="teaserD" src="papers/deformablesTeaser.png"/>
<span>ACM Transactions on Graphics (Proc. SIGGRAPH 2014)</span>
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<h2>Abstract</h2>
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<p>
We present a combined hardware and software solution for markerless reconstruction of non-rigidly deforming physical objects with arbitrary shape in real-time.
Our system uses a single self-contained stereo camera unit built from off-the-shelf components and consumer graphics hardware to generate spatio-temporally coherent 3D models at 30 Hz.  A new stereo matching algorithm estimates real-time RGB-D data. We start by scanning a smooth template model of the subject as they move rigidly.
This geometric surface prior avoids strong scene assumptions, such as a kinematic human skeleton or a parametric shape model. Next, a novel GPU pipeline performs non-rigid registration of live RGB-D data to the smooth template using an extended non-linear as-rigid-as-possible (ARAP) framework. High-frequency details are fused onto the final mesh using a linear deformation model. 
The system is an order of magnitude faster than state-of-the-art methods, while matching the quality and robustness of many offline algorithms. 
We show precise real-time reconstructions of diverse scenes, including: large deformations of users' heads, hands, and upper bodies; fine-scale wrinkles and folds of skin and clothing; and non-rigid interactions performed by users on flexible objects such as toys. 
We demonstrate how acquired models can be used for many interactive scenarios, including re-texturing, online performance capture and preview, and real-time shape and motion re-targeting.
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<h2>Extras</h2>
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Paper: <a href="papers/deformables.pdf"><img src="Images/pdf-icon.png"/>PDF</a>
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Video: <a href="papers/deformablesVideo.mp4"><img src="Images/video-icon.png"/>MP4</a>
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Google Scholar: <a href="http://scholar.google.com/scholar?hl=en&q=Real-time+Non-rigid+Reconstruction+using+an+RGB-D+Camera&btnG=&as_sdt=1%2C5&as_sdtp="><img src="Images/google-icon.png"/></a>
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BibTeX citation:
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@article{zollhoefer2014deformable,
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	title={Real-time Non-rigid Reconstruction using an RGB-D Camera},
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	author={Zollh{\"o}fer, Michael and Nie{\ss}ner, Matthias and Izadi, Shahram and Rehmann, Christoph and Zach, Christopher and Fisher, Matthew and Wu, Chenglei and Fitzgibbon, Andrew and Loop, Charles and Theobalt, Christian and Stamminger, Marc},
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	journal = {ACM Transactions on Graphics (TOG)},
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	publisher = {ACM},
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	volume = {33},
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	number = {4},
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	year = {2014}
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}
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